A novel fast fractal image coding algorithm based on texture feature

Abstract

A novel, fast fractal image coding algorithm based on the texture feature is proposed in this paper. Fractal image coding is a very promising technique for image compression. However, it has not been widely used because of the long encoding time and high computational complexity. The most fractal image encoding time is spent in determining the approximate D-block from a large D-blocks library by using the global searching method. Clustering the D-blocks library is an effective method to reduce the encoding time. First, all the D-blocks are clustered into several parts based on the new texture feature α derived from variation function; second, for each R-block, the approximate D-blocks are searched for in the same part. In the search process, we import control parameter δ; this step avoids losing the most approximate D-block for each R-block. Finally, the R-blocks whose least errors are larger than the threshold given in advance are coded by the quad tree method. We have performed a simulation with MATLABR2010a to verify the effectiveness of the proposed algorithm. The experimental results show that the proposed algorithm can be over 6 times faster than the moment-feature-based fractal image algorithm; in addition, the proposed algorithm also improves the quality of the decoded image and increases the PSNR's average value by 2 dB. The comparisons demonstrate that this method is better than the fractal image coding algorithm based on statistical features.

High-speed Image Compression Algorithm Based on Gabor Transform and Fractal Theory

“…However, due to large amount of calculation during the block matching process, it leads fractal coding algorithm very time-consuming. The accelerated fractal image coding algorithms mainly focus on the following three aspects: (1) Segmentation method of D blocks pool v, (2) Search method for D block and R block in the matching process [5,6,7], (3) The combination of fractal theory with other theories [8,9]. This paper presents a new image compression algorithms based on Gabor transform and fractal theory.…”